Shift of Volatile Organic Compounds (VOCs) in Gluten-Free Hemp-Enriched Sourdough Bread: A Metabolomic Approach

Abstract

Hemp seed flour represents a potential ingredient for protein enrichment of gluten-free bakery products, the nutritional value of which could be further increased by fermentation with sourdough or with beneficial lactic acid bacteria strains. In this study, a metabolomic approach was used to evaluate the effect of hemp seed flour addition and sourdough fermentation on the production of flavoring and health-related volatile organic compounds (VOCs) in a gluten-free bread. Multivariate analysis of VOCs provided an in-depth description of the effects of hemp seed flour addition and sourdough fermentation on flavoring and bioactive compounds. In particular, an increased concentration of antimicrobial compounds, a larger spectrum of bioactive VOCs and a typical flavoring profile was evidenced in comparison to standard products. Furthermore, an increase of fermentation metabolites was observed in comparison to a standard dough, relating to abundances of 2-butanone-3-hydroxy, acetic acid, ethanol, and 1,4-butanediol. This study provides new insights on the evolution of flavoring and bioactive hemp seed flour constituents during sourdough fermentation, evidencing their retention in baked goods, and describes a new approach that could guide the formulation of innovative, fermented food with enhanced nutritional value.

Keywords: SPME-GC-MS; bioactive compounds; flavoring compounds; gluten free; hemp; multivariate analysis; sourdough.

Figure 1

Relative quantification of total volatile organic compounds (VOCs) divided by chemical classes. Different letters indicate different significance values by Tukey’s HSD test (p < 0.05). Sample abbreviations: H = hemp seed enriched; S = standard; NF = not fermented; F = fermented; B = breads. Box = mean value; Rectangles = mean ± Standard Deviation (SD); Whiskers = mean + 1.96*SD. Black plots = alcohols; red plots = aldehydes; blue plots = ketones; green plots = organic acids; fuchsia plot = alkenes.

Figure 2

(A) Principle component analysis (PCA) of cases and variables on alcohols (p < 0.05); (B) K-means clustering analysis (at least p < 0.05).

Figure 3

(A) PCA of cases and variables on aldehydes (p < 0.05); (B) K-means clustering analysis (at least p < 0.05).

Figure 4

(A) PCA of cases and variables on ketones (p < 0.05); (B) K-means clustering analysis (at least p < 0.05).

Figure 5

(A) PCA of cases and variables on alkenes (p < 0.05); (B) K-means clustering analysis (at least p < 0.05).

Figure 6

(A) PCA of cases and variables on organic acids (p < 0.05); (B) K-means clustering analysis (p < 0.05).